com.google.api.services.bigquery.model.ArimaModelInfo Maven / Gradle / Ivy
/*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
* in compliance with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software distributed under the License
* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
* or implied. See the License for the specific language governing permissions and limitations under
* the License.
*/
/*
* This code was generated by https://github.com/googleapis/google-api-java-client-services/
* Modify at your own risk.
*/
package com.google.api.services.bigquery.model;
/**
* Arima model information.
*
* This is the Java data model class that specifies how to parse/serialize into the JSON that is
* transmitted over HTTP when working with the BigQuery API. For a detailed explanation see:
* https://developers.google.com/api-client-library/java/google-http-java-client/json
*
*
* @author Google, Inc.
*/
@SuppressWarnings("javadoc")
public final class ArimaModelInfo extends com.google.api.client.json.GenericJson {
/**
* Arima coefficients.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private ArimaCoefficients arimaCoefficients;
/**
* Arima fitting metrics.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private ArimaFittingMetrics arimaFittingMetrics;
/**
* Whether Arima model fitted with drift or not. It is always false when d is not 1.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Boolean hasDrift;
/**
* If true, holiday_effect is a part of time series decomposition result.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Boolean hasHolidayEffect;
/**
* If true, spikes_and_dips is a part of time series decomposition result.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Boolean hasSpikesAndDips;
/**
* If true, step_changes is a part of time series decomposition result.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Boolean hasStepChanges;
/**
* Non-seasonal order.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private ArimaOrder nonSeasonalOrder;
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List seasonalPeriods;
/**
* The time_series_id value for this time series. It will be one of the unique values from the
* time_series_id_column specified during ARIMA model training. Only present when
* time_series_id_column training option was used.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.String timeSeriesId;
/**
* The tuple of time_series_ids identifying this time series. It will be one of the unique tuples
* of values present in the time_series_id_columns specified during ARIMA model training. Only
* present when time_series_id_columns training option was used and the order of values here are
* same as the order of time_series_id_columns.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List timeSeriesIds;
/**
* Arima coefficients.
* @return value or {@code null} for none
*/
public ArimaCoefficients getArimaCoefficients() {
return arimaCoefficients;
}
/**
* Arima coefficients.
* @param arimaCoefficients arimaCoefficients or {@code null} for none
*/
public ArimaModelInfo setArimaCoefficients(ArimaCoefficients arimaCoefficients) {
this.arimaCoefficients = arimaCoefficients;
return this;
}
/**
* Arima fitting metrics.
* @return value or {@code null} for none
*/
public ArimaFittingMetrics getArimaFittingMetrics() {
return arimaFittingMetrics;
}
/**
* Arima fitting metrics.
* @param arimaFittingMetrics arimaFittingMetrics or {@code null} for none
*/
public ArimaModelInfo setArimaFittingMetrics(ArimaFittingMetrics arimaFittingMetrics) {
this.arimaFittingMetrics = arimaFittingMetrics;
return this;
}
/**
* Whether Arima model fitted with drift or not. It is always false when d is not 1.
* @return value or {@code null} for none
*/
public java.lang.Boolean getHasDrift() {
return hasDrift;
}
/**
* Whether Arima model fitted with drift or not. It is always false when d is not 1.
* @param hasDrift hasDrift or {@code null} for none
*/
public ArimaModelInfo setHasDrift(java.lang.Boolean hasDrift) {
this.hasDrift = hasDrift;
return this;
}
/**
* If true, holiday_effect is a part of time series decomposition result.
* @return value or {@code null} for none
*/
public java.lang.Boolean getHasHolidayEffect() {
return hasHolidayEffect;
}
/**
* If true, holiday_effect is a part of time series decomposition result.
* @param hasHolidayEffect hasHolidayEffect or {@code null} for none
*/
public ArimaModelInfo setHasHolidayEffect(java.lang.Boolean hasHolidayEffect) {
this.hasHolidayEffect = hasHolidayEffect;
return this;
}
/**
* If true, spikes_and_dips is a part of time series decomposition result.
* @return value or {@code null} for none
*/
public java.lang.Boolean getHasSpikesAndDips() {
return hasSpikesAndDips;
}
/**
* If true, spikes_and_dips is a part of time series decomposition result.
* @param hasSpikesAndDips hasSpikesAndDips or {@code null} for none
*/
public ArimaModelInfo setHasSpikesAndDips(java.lang.Boolean hasSpikesAndDips) {
this.hasSpikesAndDips = hasSpikesAndDips;
return this;
}
/**
* If true, step_changes is a part of time series decomposition result.
* @return value or {@code null} for none
*/
public java.lang.Boolean getHasStepChanges() {
return hasStepChanges;
}
/**
* If true, step_changes is a part of time series decomposition result.
* @param hasStepChanges hasStepChanges or {@code null} for none
*/
public ArimaModelInfo setHasStepChanges(java.lang.Boolean hasStepChanges) {
this.hasStepChanges = hasStepChanges;
return this;
}
/**
* Non-seasonal order.
* @return value or {@code null} for none
*/
public ArimaOrder getNonSeasonalOrder() {
return nonSeasonalOrder;
}
/**
* Non-seasonal order.
* @param nonSeasonalOrder nonSeasonalOrder or {@code null} for none
*/
public ArimaModelInfo setNonSeasonalOrder(ArimaOrder nonSeasonalOrder) {
this.nonSeasonalOrder = nonSeasonalOrder;
return this;
}
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
* @return value or {@code null} for none
*/
public java.util.List getSeasonalPeriods() {
return seasonalPeriods;
}
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
* @param seasonalPeriods seasonalPeriods or {@code null} for none
*/
public ArimaModelInfo setSeasonalPeriods(java.util.List seasonalPeriods) {
this.seasonalPeriods = seasonalPeriods;
return this;
}
/**
* The time_series_id value for this time series. It will be one of the unique values from the
* time_series_id_column specified during ARIMA model training. Only present when
* time_series_id_column training option was used.
* @return value or {@code null} for none
*/
public java.lang.String getTimeSeriesId() {
return timeSeriesId;
}
/**
* The time_series_id value for this time series. It will be one of the unique values from the
* time_series_id_column specified during ARIMA model training. Only present when
* time_series_id_column training option was used.
* @param timeSeriesId timeSeriesId or {@code null} for none
*/
public ArimaModelInfo setTimeSeriesId(java.lang.String timeSeriesId) {
this.timeSeriesId = timeSeriesId;
return this;
}
/**
* The tuple of time_series_ids identifying this time series. It will be one of the unique tuples
* of values present in the time_series_id_columns specified during ARIMA model training. Only
* present when time_series_id_columns training option was used and the order of values here are
* same as the order of time_series_id_columns.
* @return value or {@code null} for none
*/
public java.util.List getTimeSeriesIds() {
return timeSeriesIds;
}
/**
* The tuple of time_series_ids identifying this time series. It will be one of the unique tuples
* of values present in the time_series_id_columns specified during ARIMA model training. Only
* present when time_series_id_columns training option was used and the order of values here are
* same as the order of time_series_id_columns.
* @param timeSeriesIds timeSeriesIds or {@code null} for none
*/
public ArimaModelInfo setTimeSeriesIds(java.util.List timeSeriesIds) {
this.timeSeriesIds = timeSeriesIds;
return this;
}
@Override
public ArimaModelInfo set(String fieldName, Object value) {
return (ArimaModelInfo) super.set(fieldName, value);
}
@Override
public ArimaModelInfo clone() {
return (ArimaModelInfo) super.clone();
}
}